Inductive Genetic Programming with Immune Network Dynamics

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InCollection{nikolaev:1999:aigp3,

• author = "Nikolay I. Nikolaev and Hitoshi Iba and Vanio Slavov",
• title = "Inductive Genetic Programming with Immune Network Dynamics",
• booktitle = "Advances in Genetic Programming 3",
• publisher = "MIT Press",
• year = "1999",
• editor = "Lee Spector and William B. Langdon and Una-May O'Reilly and Peter J. Angeline",
• chapter = "15",
• pages = "355--376",
• address = "Cambridge, MA, USA",
• month = jun,
• keywords = "genetic algorithms, genetic programming",
• ISBN = "0-262-19423-6",
• URL = "http://www.cs.ucl.ac.uk/staff/W.Langdon/aigp3/ch15.pdf",
• DOI = "doi:10.7551/mitpress/1110.003.0020",
• size = "22 pages",
• abstract = "This chapter presents an immune version of Genetic Programming (GP). This is a GP version that conducts progressive search controlled by a dynamic fitness function. The new fitness function is based on analogy with a model of the biological immune system, such that the programs are viewed as lymphocyte clones that compete to recognize most of the examples, viewed as antigens. The programs are reinforced with rewards for matched important examples and stimulated to match different examples. Examples recognized by a small number of programs are considered important. The motivation for using the immune dynamics for GP navigation is to maintain a high population diversity and to achieve enhanced search performance. Empirical evidence for the efficacy of this immune version on practical inductive machine learning and time-series prediction tasks is provided",
• notes = "AiGP3 See http://cognet.mit.edu",

}

Genetic Programming entries for Nikolay Nikolaev Hitoshi Iba Vanio Slavov

Citations